Here is some good amazing zing zing…intro for u

Aaj kal diff devics r used for data.Here i am expliining aboyut forth week assign of practical machie lerning.I hope u unaderstaning all this cudeeee.

```r
v_1 <- read.csv("C:\\Users\\HP\\Downloads\\pml-training.csv", stringsAsFactors = F,na.strings = c("","NA","#DIV/0!"))
v_2 <- read.csv("C:\\Users\\HP\\Downloads\\pml-testing.csv", stringsAsFactors = F,na.strings = c("","NA","#DIV/0!"))
dim(v_1); dim(v_2)
```

```
## [1] 19622   160
```

```
## [1]  20 160
```







```r
#for reproducability
set.seed(101)
v_3 <- createDataPartition(v_1$classe, p = 0.8, list = F)
v_6 <- v_1[-v_3,]
v_1 <- v_1[v_3,]
dim(v_1); dim(v_6)
```

```
## [1] 15699   160
```

```
## [1] 3923  160
```





```r
table(v_1$classe)/nrow(v_1)
```

```
## 
##         A         B         C         D         E 
## 0.2843493 0.1935155 0.1744060 0.1638958 0.1838334
```





```r
v_4 <- sapply(select(v_1,names(v_1)[grepl("_belt",names(v_1))]),
                    function(x) sum(is.na(x)))
v_4
```

```
##            roll_belt           pitch_belt             yaw_belt 
##                    0                    0                    0 
##     total_accel_belt   kurtosis_roll_belt  kurtosis_picth_belt 
##                    0                15396                15413 
##    kurtosis_yaw_belt   skewness_roll_belt skewness_roll_belt.1 
##                15699                15395                15413 
##    skewness_yaw_belt        max_roll_belt       max_picth_belt 
##                15699                15388                15388 
##         max_yaw_belt        min_roll_belt       min_pitch_belt 
##                15396                15388                15388 
##         min_yaw_belt  amplitude_roll_belt amplitude_pitch_belt 
##                15396                15388                15388 
##   amplitude_yaw_belt var_total_accel_belt        avg_roll_belt 
##                15396                15388                15388 
##     stddev_roll_belt        var_roll_belt       avg_pitch_belt 
##                15388                15388                15388 
##    stddev_pitch_belt       var_pitch_belt         avg_yaw_belt 
##                15388                15388                15388 
##      stddev_yaw_belt         var_yaw_belt         gyros_belt_x 
##                15388                15388                    0 
##         gyros_belt_y         gyros_belt_z         accel_belt_x 
##                    0                    0                    0 
##         accel_belt_y         accel_belt_z        magnet_belt_x 
##                    0                    0                    0 
##        magnet_belt_y        magnet_belt_z 
##                    0                    0
```



```r
v_5 <- sapply(select(v_1,names(v_1)[grepl("_arm",names(v_1))]),
                   function(x) sum(is.na(x)))
v_5
```

```
##            roll_arm           pitch_arm             yaw_arm     total_accel_arm 
##                   0                   0                   0                   0 
##       var_accel_arm        avg_roll_arm     stddev_roll_arm        var_roll_arm 
##               15388               15388               15388               15388 
##       avg_pitch_arm    stddev_pitch_arm       var_pitch_arm         avg_yaw_arm 
##               15388               15388               15388               15388 
##      stddev_yaw_arm         var_yaw_arm         gyros_arm_x         gyros_arm_y 
##               15388               15388                   0                   0 
##         gyros_arm_z         accel_arm_x         accel_arm_y         accel_arm_z 
##                   0                   0                   0                   0 
##        magnet_arm_x        magnet_arm_y        magnet_arm_z   kurtosis_roll_arm 
##                   0                   0                   0               15446 
##  kurtosis_picth_arm    kurtosis_yaw_arm   skewness_roll_arm  skewness_pitch_arm 
##               15448               15398               15445               15448 
##    skewness_yaw_arm        max_roll_arm       max_picth_arm         max_yaw_arm 
##               15398               15388               15388               15388 
##        min_roll_arm       min_pitch_arm         min_yaw_arm  amplitude_roll_arm 
##               15388               15388               15388               15388 
## amplitude_pitch_arm   amplitude_yaw_arm 
##               15388               15388
```





```r
v_7 <- sapply(select(v_1,
                              names(v_1)[grepl("_forearm",names(v_1))]),
                       function(x) sum(is.na(x)))
v_7
```

```
##            roll_forearm           pitch_forearm             yaw_forearm 
##                       0                       0                       0 
##   kurtosis_roll_forearm  kurtosis_picth_forearm    kurtosis_yaw_forearm 
##                   15448                   15449                   15699 
##   skewness_roll_forearm  skewness_pitch_forearm    skewness_yaw_forearm 
##                   15447                   15449                   15699 
##        max_roll_forearm       max_picth_forearm         max_yaw_forearm 
##                   15388                   15388                   15448 
##        min_roll_forearm       min_pitch_forearm         min_yaw_forearm 
##                   15388                   15388                   15448 
##  amplitude_roll_forearm amplitude_pitch_forearm   amplitude_yaw_forearm 
##                   15388                   15388                   15448 
##     total_accel_forearm       var_accel_forearm        avg_roll_forearm 
##                       0                   15388                   15388 
##     stddev_roll_forearm        var_roll_forearm       avg_pitch_forearm 
##                   15388                   15388                   15388 
##    stddev_pitch_forearm       var_pitch_forearm         avg_yaw_forearm 
##                   15388                   15388                   15388 
##      stddev_yaw_forearm         var_yaw_forearm         gyros_forearm_x 
##                   15388                   15388                       0 
##         gyros_forearm_y         gyros_forearm_z         accel_forearm_x 
##                       0                       0                       0 
##         accel_forearm_y         accel_forearm_z        magnet_forearm_x 
##                       0                       0                       0 
##        magnet_forearm_y        magnet_forearm_z 
##                       0                       0
```



```r
v_8 <- sapply(select(v_1,
                               names(v_1)[grepl("_dumbbell",names(v_1))]),
                        function(x) sum(is.na(x)))
v_8
```

```
##            roll_dumbbell           pitch_dumbbell             yaw_dumbbell 
##                        0                        0                        0 
##   kurtosis_roll_dumbbell  kurtosis_picth_dumbbell    kurtosis_yaw_dumbbell 
##                    15392                    15390                    15699 
##   skewness_roll_dumbbell  skewness_pitch_dumbbell    skewness_yaw_dumbbell 
##                    15391                    15389                    15699 
##        max_roll_dumbbell       max_picth_dumbbell         max_yaw_dumbbell 
##                    15388                    15388                    15392 
##        min_roll_dumbbell       min_pitch_dumbbell         min_yaw_dumbbell 
##                    15388                    15388                    15392 
##  amplitude_roll_dumbbell amplitude_pitch_dumbbell   amplitude_yaw_dumbbell 
##                    15388                    15388                    15392 
##     total_accel_dumbbell       var_accel_dumbbell        avg_roll_dumbbell 
##                        0                    15388                    15388 
##     stddev_roll_dumbbell        var_roll_dumbbell       avg_pitch_dumbbell 
##                    15388                    15388                    15388 
##    stddev_pitch_dumbbell       var_pitch_dumbbell         avg_yaw_dumbbell 
##                    15388                    15388                    15388 
##      stddev_yaw_dumbbell         var_yaw_dumbbell         gyros_dumbbell_x 
##                    15388                    15388                        0 
##         gyros_dumbbell_y         gyros_dumbbell_z         accel_dumbbell_x 
##                        0                        0                        0 
##         accel_dumbbell_y         accel_dumbbell_z        magnet_dumbbell_x 
##                        0                        0                        0 
##        magnet_dumbbell_y        magnet_dumbbell_z 
##                        0                        0
```



```r
v_9 <- c(names(v_4[v_4 != 0]), 
                  names(v_5[v_5 != 0]),
                  names(v_7[v_7 != 0]),
                  names(v_8[v_8 != 0]))
length(v_9)
```

```
## [1] 100
```



```r
#dropping the cols
v_10 <- tbl_df(v_1 %>% 
                      select(-v_9,
                             -c(X,user_name, raw_timestamp_part_1, 
                                raw_timestamp_part_2, cvtd_timestamp, 
                                new_window,num_window)))
```

```
## Warning: `tbl_df()` is deprecated as of dplyr 1.0.0.
## Please use `tibble::as_tibble()` instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_warnings()` to see where this warning was generated.
```

```
## Note: Using an external vector in selections is ambiguous.
## i Use `all_of(v_9)` instead of `v_9` to silence this message.
## i See <https://tidyselect.r-lib.org/reference/faq-external-vector.html>.
## This message is displayed once per session.
```

```r
v_10$classe <- as.factor(v_10$classe)
v_10[,1:52] <- lapply(v_10[,1:52],as.numeric)
dim(v_10)
```

```
## [1] 15699    53
```



```r
v_11 <- cor(select(v_10, -classe))
diag(v_11) <- 0
v_11 <- which(abs(v_11)>0.8,arr.ind = T)
v_11 <- unique(row.names(v_11))
corrplot(cor(select(v_10,v_11)),
         type="upper", order="hclust",method = "number")
```

```
## Note: Using an external vector in selections is ambiguous.
## i Use `all_of(v_11)` instead of `v_11` to silence this message.
## i See <https://tidyselect.r-lib.org/reference/faq-external-vector.html>.
## This message is displayed once per session.
```

<img src="practical_ml_files/figure-html/unnamed-chunk-11-1.png" width="960" />



```r
#nfbdyhfgyfhwuiiofjekj
#sjhgfaehfghfgurfhruigherjgheoi
v_12 <- v_10 %>% binarize(n_bins = 4, thresh_infreq = 0.01)
```



```r
v_13<- v_12 %>% correlate(target = classe__A) 
v_13%>% plot_correlation_funnel(interactive = T,limits = c(-0.5,0.5))
```

```r v_15<- v_12 %>% correlate(target = classe__B) v_15%>% plot_correlation_funnel(interactive = T,limits = c(-0.5,0.5)) ```
```r v_18<- v_12 %>% correlate(target = classe__C) v_18%>% plot_correlation_funnel(interactive = T,limits = c(-0.5,0.5)) ```
```r v_21<- v_12 %>% correlate(target = classe__D) v_21%>% plot_correlation_funnel(interactive = T,limits = c(-0.5,0.5)) ```
```r v_23 <- v_12 %>% correlate(target = classe__E) v_23 %>% plot_correlation_funnel(interactive = T,limits = c(-0.5,0.5)) ```
```r #subseting v_10 v_25 <- c("magnet_arm_x", "pitch_forearm" , "magnet_dumbbell_y", "roll_forearm", "gyros_dumbbell_y") v_26<- c("magnet_dumbbell_y", "magnet_dumbbell_x" , "roll_dumbbell" , "magnet_belt_y" , "accel_dumbbell_x" ) v_27 <- c("magnet_dumbbell_y", "roll_dumbbell" , "accel_dumbbell_y" , "magnet_dumbbell_x", "magnet_dumbbell_z") v_28 <- c("pitch_forearm" , "magnet_arm_y" , "magnet_forearm_x", "accel_dumbbell_y", "accel_forearm_x") v_29 <- c("magnet_belt_y" , "magnet_belt_z" , "roll_belt", "gyros_belt_z" , "magnet_dumbbell_y") flsks_cols_qwef <- character() for(c in c(v_25,v_26,v_27,v_28,v_29)){ flsks_cols_qwef <- union(flsks_cols_qwef, c) } v_102 <- v_10 %>% select(flsks_cols_qwef, classe) ``` ``` ## Note: Using an external vector in selections is ambiguous. ## i Use `all_of(flsks_cols_qwef)` instead of `flsks_cols_qwef` to silence this message. ## i See <https://tidyselect.r-lib.org/reference/faq-external-vector.html>. ## This message is displayed once per session. ``` ```r data.frame("arm" = sum(grepl("_arm",flsks_cols_qwef)), "forearm" = sum(grepl("_forearm",flsks_cols_qwef)), "belt" = sum(grepl("_belt",flsks_cols_qwef)), "dumbbell" = sum(grepl("_dumbbell",flsks_cols_qwef))) ``` <div data-pagedtable="false"> <script data-pagedtable-source type="application/json"> {"columns":[{"label":["arm"],"name":[1],"type":["int"],"align":["right"]},{"label":["forearm"],"name":[2],"type":["int"],"align":["right"]},{"label":["belt"],"name":[3],"type":["int"],"align":["right"]},{"label":["dumbbell"],"name":[4],"type":["int"],"align":["right"]}],"data":[{"1":"2","2":"4","3":"4","4":"7"}],"options":{"columns":{"min":{},"max":[10]},"rows":{"min":[10],"max":[10]},"pages":{}}} </script> </div>